Proceedings of the Advances in Materials, Machinery, Electrical Engineering (AMMEE 2017)

Research on Improved Genetic Algorithm for Virus Intrusion Detection Model

Authors
Peng Zhang
Corresponding Author
Peng Zhang
Available Online June 2017.
DOI
https://doi.org/10.2991/ammee-17.2017.139How to use a DOI?
Keywords
improved genetic algorithm; intrusion detection model; traditional security model; computer virus.
Abstract
The purpose of this study is to solve the computer security problems. Based on the traditional security model, the hidden dangers of computer security and the advantages and disadvantages of various intrusion detection techniques are analyzed. A computer intrusion detection system based on an improved genetic algorithm is designed. The results show that the optimized genetic algorithm can improve the efficiency of intrusion detection and reduce the false alarm rate. Therefore, we conclude that the application of genetic algorithm in intrusion detection has important theoretical and practical significance.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
Advances in Materials, Machinery, Electrical Engineering (AMMEE 2017)
Part of series
Advances in Engineering Research
Publication Date
June 2017
ISBN
978-94-6252-350-0
ISSN
2352-5401
DOI
https://doi.org/10.2991/ammee-17.2017.139How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Peng Zhang
PY  - 2017/06
DA  - 2017/06
TI  - Research on Improved Genetic Algorithm for Virus Intrusion Detection Model
BT  - Advances in Materials, Machinery, Electrical Engineering (AMMEE 2017)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/ammee-17.2017.139
DO  - https://doi.org/10.2991/ammee-17.2017.139
ID  - Zhang2017/06
ER  -